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Wednesday, December 23, 2015

A colleague recently inquired as to how one might go about interpreting
the pattern shown by a so-called disparity-through-time (DTT) plot.

A DTT plot shows the mean disparity (effectively, variance) of each subtree
compared to the total disparity, and is calculated by taking a time slice at
each 'event' (speciation event recorded in the reconstructed phylogeny) of
the tree.

DTT plots are interpreted in a variety of ways in the literature - for
instance, as evidence that variability accumulates within, rather than
between, clades; or that phenotypic diversity has tended to accrue in the
early rather than the later stages of a diversification.

I thought it might be nonetheless useful to conduct a 'mini' simulation study
in which I examined how, in general, the accumulation of disparity among
clades through time may be related to biological process.

To start with, here are a couple of small custom functions that I wrote
to facilitate the analyses:

## Brownian motion with a trend
X<-lapply(trees,fastBM,mu=4)
D<-mapply(dtt,trees,X,MoreArgs=list(plot=FALSE),SIMPLIFY=FALSE)
plotDtt(D,main="BM with a trend")

Finally, it is important to keep in mine that DTT plots can be pretty
substantially affected by sampling error in the estimation of species
means. Here is a demo of the effect of two different levels of sampling
error. I have simulated sampling variances from a exponential distribution
with rate 1.0, but then multiplied by different values of a constant
k, in which larger values imply more sampling error:

About this blog

This web-log chronicles the development of new tools for phylogenetic analyses in the phytools R package. Unless you a reading a very recent page of the blog, I recommend that you install the latest CRAN version of phytools (or latest beta release) before attempting to replicate any of the analyses of this site. That is because the linked functions may be archived, and very likely have been replaced by newer versions.